Transcript Minimum-Cost QoS-Constrained Deployment and Routing Policies for Wireless Relay

Minimum-Cost QoS-Constrained Deployment
and Routing Policies for Wireless Relay
Networks of Maximal Ratio Combining
Capacities
考慮服務品質限制之具最大比率合成能力
中繼站無線網路成本最小化建置與路由策略
Advisor: Lin Yeong-Sung, Ph.D.
Chu Kuo-Chung, Ph.D.
Presented by Hermes Y.H. Liu
2016/6/13
OPLab, IM, NTU
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Agenda



Introduction and Motivation
Problem Description
Problem Formulation
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Introduction and Motivation
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Introduction

Relay technology has been used widely in wireless
communication, such as IEEE 802.16j, IEEE 802.11s, and
seed concept in 3GPP

Advantages of relay:
1. radio range extension
2. overcome shadow fading
3. reduce infrastructure deployment costs
4. enhance capacity
5. reduce outage probability
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Relay
Figure: Left: tree topology in relay network; Right: mesh topology in mesh network
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Relay (contd.)

Relays are designed to improve the coverage of a BS and
overcome the shadows caused by obstacles.
R
R
R
R
Figure: City scenario of relays deployment with one BS
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Relay (contd.)

three types of relay protocols:
1. Amplify-and-Forward : Relays act as analog repeaters by
retransmitting an amplified version of their received signals. The
noise is amplified as well.
2. Decode-and-Forward: Relays attempt to decode, regenerate and
retransmit the same information from the original source, the
propagating decoding errors may occur.
3. Decode-and-Reencode: Relays attempt to decode, reencode the
received signals with codewords that are different from the received
codewords. Again, there is the probability of error propagation.
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IEEE 802.16j

IEEE 802.16j is now a developing specification established by
IEEE 802.16j task group

the enhancement of original 802.16-2004/802.16e-2005

Compatible to the legacy standard

A relay station (RS) will be recognized as a base station (BS)
by the mobile station (MSs) for the transparency reasons
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IEEE 802.16j (contd.)
Fixed Infrastructure Usage Model
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Temporary Coverage Usage Model
In-Building Coverage Usage Model
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Coverage on Mobile Vehicle Usage Models
Diversity Techniques

Frequency diversity: transmitting or receiving the signal at
different frequencies;

Time diversity: transmitting or receiving the signal at different
times;

Space diversity: transmitting or receiving the signal at different
locations;

Polarization diversity: transmitting or receiving the signal with
different polarizations.
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Cooperative Diversity

Cooperative diversity is a relatively new class of spatial
diversity techniques that is enabled by relaying

to improve the reliability of communications in terms of, for
example, outage probability, or symbol-or bit-error probability,
for a given transmission rate
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Diversity Signal-processing
Techniques

selection diversity (SD)

equal gain combining (EGC)

maximal ratio combining (MRC)
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Maximal Ratio Combining (MRC)
Figure: Maximal ratio combining
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Motivation
Figure: Left: single-stage concept; Right: multistage concept
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Motivation

Allow multiple source nodes jointly transmit one single
information if the signal strength is not robust enough in the
link between one source node to the destination

The routing policy is no longer a single path but with more
complex multicast-tree algorithms
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Problem Description
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Problem Description
BS
MC
r
r
r
MC
BS
r
BS
Figure: Network separations with several BSs
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Problem Description (contd.)
DL Transmission
r
r
MC
BS
r
Figure: DL transmission tree and one OD pair routing subtree
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Problem Description (contd.)
UL Transmission
r
MC
BS
r
Figure: UL transmission tree and one OD pair routing subtree
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Problem Description (contd.)

In this paper, we try to find a near optimal relays development
policy to minimize the total development costs; meanwhile, to
maintain both DL and UL spanning trees and using multicasttree based routing algorithm to ensure the bit error probability
(BEP) and data rate requirements of each mobile cluster must
be satisfied.
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Problem Formulation
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Problem Formulation
Assumption:








The relaying protocol in this model is Decode-and-Forward
Each mobile cluster (MC) must home to either a BS or relay(s)
The relays selected by one MC must associate with the same BS
The routing path of each OD pair in DL (UL) is a subtree of the DL
(UL) spanning tree
The spatial diversity gains are represented by the aggregate SNRs
with MRC techniques
The BEP of a transmission is measured by the receiving SNR value
The aggregate BEPs of the destination are the summation of BEPs of
each node on the routing subtree
The numbers of links of each path adopted by each MC are assumed
to be equal to ensure the MRC is achievable within limited delay
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Problem Formulation (contd.)
Objective:

To minimize the total cost of wireless relay network deployment
Subject to:

Relay selection constraints

Nodal capacity constraints

Cooperative relaying constraints in DL and UL

Routing constraints in DL and UL

Link capacity constraints in DL and UL
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Problem Formulation (contd.)
To determine:




Whether or not a location should be selected to build a relay
The DL and UL spanning trees
The cooperative relays of each MC
The subtree , which is on the spanning tree, selected by each MC
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Problem Formulation (contd.)
Given Parameters
Notion
Description
General
B
The set of base stations, where b B
R
The set of candidate locations, where r  R
K
The set of relay configurations, where k  K
N
The set of mobile clusters, where n  N
 ndir
The data rate required to be transmitted of mobile cluster n in direction
dir in (packets/sec)
r
The fix cost of building relay on location r
 r (k )
The configured cost of building relay r , which is a function of
configuration k
An arbitrarily large number
M1
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Problem Formulation (contd.)
Spanning tree
Tb
The set of all spanning trees rooted at base station b , where t  Tb
Pbr
The set of paths from base station b to relay r , where p  Pbr
 puv
The indicator function which is 1 if link uv is on path p and 0
 tuv
The indicator function which is 1 if link uv is on tree t and 0
otherwise
otherwise
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Problem Formulation (contd.)
SNR and attenuation
Duv
The distance of link uv

L( Duv , )
Attenuation factor
Attenuation rate, which is a function of Duv and 
PNI
The thermal noise and interference strength
 bB
Transmit power of base station b
 nN
Transmit power of mobile cluster n
 rdir (k )
Transmit power of relay r in direction dir , which is a function of
configuration k
N
 min
The minimum SNR requirement for a mobile cluster to receive from a
relay in DL
R
 min
The minimum SNR requirement for a relay to receive from a mobile
cluster in UL
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Problem Formulation (contd.)
BEP
BEP dir
The BEP requirement for the transmission received by a destination in
direction dir where the destination in DL is MC and in UL is BS
BEPs ( SNR)
The BEP value of each node s , which is a function of the receiving
SNR, where s  {R  B  N }
Capacity
The nodal capacity of base station b in (packets/sec)
Cb
Cr (k )
Cuv ( SNR)
The nodal capacity of relay r in (packets/sec), which is a function of
configuration k
The capacity of link uv in (packets/sec), which is a function of the
receiving SNR of node v , where u, v  {R  B}
Relaying
SD dir
The maximum spatial diversity of a mobile cluster in direction dir
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Problem Formulation (contd.)
Decision Variables
Notion
Description
rk
1 if candidate location r is selected to build a relay with configuration
k and 0 otherwise
hrbdir
1 if relay r associates with base station b in direction dir and 0
otherwise
 nsdir
1 if node s is selected to relay mobile cluster n in direction dir
and 0 otherwise, where s {R  B}
dir
ynuv
1 if link uv is on the subtree adopted by mobile cluster n in direction
dir and 0 otherwise
1 if path p is selected from base station b to relay r in direction
dir and 0 otherwise, where p  Pbr
xdir
p
1 if spanning tree t is selected to be shared by all relays in direction
ztdir
dir and 0 otherwise
The aggregate flow of link uv in direction dir
f uvdir
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Problem Formulation (contd.)
Auxiliary Variables
Notion
dir
nrp
Description
1 if relay r is selected by mobile cluster n and path p is selected
by relay r in direction dir and 0 otherwise, where n  N , r  R ,
p  Pbr
The SNR received by node v in link uv , where u, v  {R  B}
uvdir
The SNR received by node v in link uv , where u {R  B}, v  N
in DL; and u  N , v  {R  B} in UL
 uvDL
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Objective function:
min   ( r   r (k ))rk
rR kK
(IP 1)
Subject to: (General Constraint)
Relay selection constraints
1
r  R
(2.1)
1
r  R
(2.2)
UL
h
 rb  1
r  R
(2.3)
hrbDL   rk
r  R, b  B
(2.4)
hrbUL  rk
r  R, b  B
(2.5)

kK
h
bB
rk
DL
rb
bB
kK
kK
Nodal capacity constraints
furDL  f rwUL   rk Cr (k )
r  R, u, w  {R  B}
(2.6)
b B
(2.7)
r  R, k  K
r  R, b  B
(2.8)
(2.9)
r  R, b  B
(2.10)
kK

rR
UL UL
fbrDL    nbDL nDL   fibUL    mb
 m  Cb
nN
Integer constraints
rk  0 or 1
DL
rb
h
 0 or 1
hrbUL  0 or 1
iR
nN
(DL Constraint)
Cooperative relay constraints (DL)
DL
DL



 nb nr  1
n  N , r  R
(2.11)
n  N , s  {R  B}
(2.12)
n  N , s  {R  B}
(2.13)
n  N
(2.14)
u , v  {R  B}
(2.15)
bB
1

s{ R  B }
 
DL
ns
N
min
 nsDL

DL
sn
  
DL
DL
y
BEP

 nuv v uv 
vR
DL


 uk u (k )
kK
L  Duv , 
PNI
 uvDL
s{ R  B}
 nsDL BEPn  snDL   BEP DL
0 

DL
uv
DL


 sk s (k )
u , v  {R  B}
(2.16)
s  {R  B}, n  N
(2.17)
s  {R  B}, n  N
(2.18)
n  N
(2.19)
kK
L  Dsn , 
PNI
0

rR
DL
sn
DL
nr

 SD DL
  snDL
Routing constraints (DL)
k
DL
nr
h
DL
rb
hrbDL 

pPbr
x
bB pPbr
 x
DL
nr
DL
p
x pDL
DL
p
1

DL
nrp
n  N , r  R, b  B
(2.20)
r  R, b  B
(2.21)
r  R
(2.22)
n  N , r  R,
p  Pbr , b  B
(2.23)
  
pPbi u{ R  B} v{ R  B}

DL
nip
 puv 
  
pPbj u{ R  B} v{ R  B}
DL
njp
 puv
n  N , i, j  R, b  B
(2.25)
n  N , u {R  B},
vR
n  N , r  R,
u , v  {R  B}
(2.26)

 1   njDL M 1
DL
ynuv
  vk
kK

bB pPbr
DL
 puv  ynuv
DL
nrp
(2.27)
DL
ynuv
  tuv ztDL
n  N , u, v  {R  B} (2.28)
z
b B
bB tTb
tTb
DL
t
1
(2.29)
Link capacity constraints (DL)
y
nN

DL DL
nuv n
 fuvDL
 
fuvDL  Cuv uvDL
u {R  B}, v  R
(2.30)
u {R  B}, v  R
(2.31)
n  N , s  {R  B}
(2.32)
p  Pbr , b  B, r  R
(2.33)
n  N , r  R,
p  Pbr , b  B
(2.34)
t  Tb , b  B
(2.35)
n  N , u, v  {R  B}
(2.36)
Integer constraints (DL)

DL
ns
x
DL
p

DL
nrp
 0 or 1
 0 or 1
 0 or 1
ztDL  0 or 1
DL
ynuv
 0 or 1
(UL Constraint)
Cooperative relay constraints (UL)

bB
1
UL
nb
n  N , r  R
  nrUL  1

s{ R  B}
n  N , s  {R  B} (2.38)
 nsUL
n  N , s  {R  B} (2.39)
R
UL
 nsUL  min
  ns

UL UL 
UL UL
UL n  N
BEP
y


BEP



BEP


v   nuv uv 
s
ns
ns
v{ R  B}
 uR
 s{R B}

kK
PNI

u , v  {R  B}
UL


 uk u (k )
L  Duv , 
(2.37)
 uvUL
(2.40)
(2.41)
0 
UL
uv

 nN
L  Dns , 
PNI
0

rR
UL
ns
UL
nr
u , v  {R  B}
(2.42)
n  N , s  {R  B}
(2.43)
n  N , s  {R  B}
(2.44)
n  N
(2.45)
  nsUL

 SDUL
Routing constraints (UL)
k
UL
nr
h
hrbUL 
UL
rb
x
UL
p
pPbr
x
bB pPbr
UL
p
1
 x 
UL UL
nr p
UL
nrp
n  N , r  R, b  B
(2.46)
r  R, b  B
(2.47)
r  R
(2.48)
n  N , r  R,
p  Pbr , b  B
(2.49)
  
pPbi u{ R  B} v{ R  B}

UL
nip
 puv 
  
pPbj u{ R  B} v{ R  B }
UL
njp
 puv
n  N , i, j  R, b  B (2.51)

 1   nrUL M 2
UL
ynuv
 uk
n  N , u  R,
v  {R  B}
(2.52)

n  N , r  R,
u , v  {R  B}
(2.53)
kK
bB pPbr
UL
 puv  ynuv
UL
nrp
UL
ynuv
   tuv ztUL
n  N , u, v  {R  B} (2.54)
z
b B
bB tTb
tTb
UL
t
1
(2.55)
Link capacity constraints (UL)
u  R, v {R  B}
(2.56)
u  R, v {R  B}
(2.57)
n  N , s  {R  B}
(2.58)
xUL
p  0 or 1
n  N , r  R,
p  Pbr , b  B
(2.59)

n  N , r  R,
p  Pbr , b  B
(2.60)
t  Tb , b  B
(2.61)
n  N , u, v  {R  B}
(2.62)
y
nN
f
UL
uv

UL UL
nuv n
 fuvUL
 
 Cuv 
UL
uv
Integer constraints (UL)
 nsUL  0 or 1
UL
nrp
z
UL
t
y
UL
nuv
 0 or 1
 0 or 1
 0 or 1
Optimal Problem (LR):
constraints (3), (4), (5), (8), (11), (12), (13), (15), (18), (20), (21), (22),
(23), (24), (25), (27), (28), (33), (36), (37), (38), (40), (43), (45), (46), (47),
(48), (49), (50), (52) and (53) are relaxed by introducing Lagrangean
multiplier vector
1 ~ 31 .
Subproblem 1 (related to decision variable rk )
Z sub 3.1 ( 1 ,  2 , 3 ,  4 , 7 , 8 , 10 , 18 ,  21 ,  24 )
 
 
  
 

1
2
3
      (k )      
 
ruw Cr (k ) 

r
r
r
r
  rR 
 
u{ R  B} w{ R  B}

 
 
DL
UL

 
 r (k )
r (k ) 
 


 
 
L
D
,

L
D
,





 
rv
rv
7
21

 rk 
 min        rv
  rv

PNI
PNI
 
 kK  r{ R  B} v{R  B} 


 
 


 
 
DL
 
 r (k )
 
 
 
L
D
,



rn
14
28 
     nr8











nur
nrv


PNI
  nN r{ R  B}
nN u{ R  B} rR
nN rR v{ R  B }
 
(Sub 3.1)
subject to:

kK
rk
1
rk  0 or 1
r  R
(Sub 3.1.1)
r  R, k  K
(Sub 3.1.2)
Subproblem 2 (related to decision variables  nsDL , x pDL ,  snDL )
Z sub 3.2 ( 3 , 4 , 5 , 6 , 5 , 9 , 11 , 12 , 13 )
3
 

 suw
 nsDL nDL    s4   nsDL nDL


 sR u{ R  B} w{ R  B}

nN
sB
nN

5
DL N
6
DL
DL
9
DL 







BEP




  nsb ns 
   ns ns min  n  ns
n  sn 
nN
s{ R  B }
nN sR bB
 nN s{ R  B}
 min 

11
DL DL
12
DL



x



M
     nrpb ns p



nisb ns
1
n

N
s

R
p

P
b

B
n

N
i

R
s

R
b

B


br


13 DL



M
 nis ns 2
 n

 N iR sR

(Sub 3.2)
Subject to:

DL
nb
  nrDL  1
n  N , r  R
(Sub 3.2.1)
n  N , s  {R  B}
(Sub 3.2.2)
n  N
(Sub 3.2.3)
n  N , r  R, b  B
(Sub 3.2.4)
x pDL  0 or 1
p  Pbr , b  B, r  R
(Sub 3.2.5)
 nsDL  0 or 1
n  N , s  {R  B}
(Sub 3.2.6)
bB
1

s{ R  B }

rR
DL
nr
 SD DL
x
bB pPbr
 nsDL
DL
p
1
UL
UL
Subproblem 3 (related to decision variables  ns
, xUL
p ,  sn )
Z sub 3.2 ( 3 , 4 , 19 , 20 , 23 , 25 , 26 , 27 )
3
 

 suw
 nsUL nUL    s4   nsUL nUL


 sR u{ R  B} w{R  B}

nN
sB
nN

19 UL R
20
UL UL
23 UL 
   ns  ns  min    n  BEPS  ns  sn      nsb ns 
nN
s{ R  B }
nN sR bB
 nN s{R  B}

 min 

25
UL DL
26
UL
     nrpb ns x p    nisb ns M 1

n

N
s

R
p

P
b

B
n

N
i

R
s

R
b

B


br


27 UL



M
 nis ns 2
 n

 N iR sR

(Sub 3.3)
Subject to:
UL
UL



 nb nr  1
n  N , r  R
(Sub 3.3.1)
n  N , s  {R  B}
(Sub 3.3.2)
n  N
(Sub 3.3.3)
n  N , r  R, b  B
(Sub 3.3.4)
xUL
p  0 or 1
p  Pbr , b  B, r  R
(Sub 3.3.5)
 nsUL  0 or 1
n  N , s  {R  B}
(Sub 3.3.6)
bB
1

s{ R  B}

rR
UL
nr
 SDUL
x
bB pPbr
 nsUL
UL
p
1
Subproblem 4 (related to decision variable fuvDL )
Z sub ( 2 , 3 , 16 , 17 )



 DL
2
16
17
3
DL 
 min      uvw
 uv
 uv
f


f
 uv  uv uv 
uB vR
u{R B} vR  w{R  B}


Subject to:
f
DL
uv
0
u {R  B}, v  R
(Sub 3.4.1)
(Sub 3.4)
Subproblem 5 (related to decision variable f uvUL )
Z sub ( 2 , 3 , 30 , 31 )



 UL
2
30
31
3
UL 
 min     uvw  uv  uv  fuv   uv fuv 
uR vB
uR v{R  B}  w{R  B}


Subject to:
fuvUL  0
u  R, v {R  B}
(Sub 3.5.1)
(Sub 3.5)
DL
Subproblem 6 (related to decision variable nrp
)
Z sub ( 11 , 12 , 13 , 15 )
11
DL
     nrpb

nrp
 nN rR pPbr bB


12
DL
12
DL 






   nrjb  nrp   nirb  nrp 
pPbi
nN iR rR bB
pPbj
 nN rR jR bB

 min 

13
DL
   nrj     nrp puv

bB pPbr u{ R  B } v{ R  B }
 nN rR jR

13
DL


nir     nrp puv


 nN iR rR

bB pPbr u{ R  B} v{ R  B }


Subject to:

pPbr

DL
nrp
DL
nrp
1
 0 or 1
n  N , r  R, b  B
(Sub 3.6.1)
n  N , r  R,
p  Pbr , b  B
(Sub 3.6.2)
(Sub 3.6)
UL
Subproblem 7 (related to decision variable nrp
)
Z sub ( 11 , 12 , 13 , 15 )
11
DL
     nrpb

nrp
 nN rR pPbr bB


12
DL
12
DL 






   nrjb  nrp   nirb  nrp 
pPbi
nN iR rR bB
pPbj
 nN rR jR bB

 min 

13
DL
   nrj     nrp puv

n

N
r

R
j

R
b

B
p

P
u

{
R

B
}
v

{
R

B
}
br


13
DL


nir     nrp puv


 nN iR rR

bB pPbr u{ R  B} v{ R  B }


Subject to:

pPbr

UL
nrp
UL
nrp
1
 0 or 1
n  N , r  R, b  B
(Sub 3.7.1)
n  N , r  R,
p  Pbr , b  B
(Sub 3.7.2)
(Sub 3.7)
DL
Subproblem 8 (related to decision variable ynuv
, uvDL )
Z sub ( 6 , 7 , 10 , 14 , 15 , 16 , 17 )


6
DL
DL
7 DL
10
DL

y
B
EP






y
  n  nuv





v
uv
uv uv
nuv nuv 
n

N
v

R
u

{
R

B
}
v

{
R

B
}
n

N
u

{
R

B
}
v

{
R

B
}




14
DL
15
DL
 min      nruv
ynuv
    nuv
ynuv

n

N
r

R
u

{
R

B
}
v

{
R

B
}
n

N
u

{
R

B
}
v

{
R

B
}




16
DL DL
17
UL

y



C






uv
nuv
n
uv
uv
uv
 u{ R  B} v{ R  B} nN

u{ R  B} v{ R  B }


 
 
(Sub 3.8)
Subject to:
0  uvDL  
u , v  {R  B}
(Sub 3.8.1)
DL
ynuv
 0 or 1
n  N , u, v  {R  B}
(Sub 3.8.2)
UL
UL
Subproblem 9 (related to decision variable ynuv
)
, uv
Z sub ( 20 , 21 , 24 , 28 , 29 , 30 , 31 )



20
UL DL 
21 UL
24 UL

BEP
y






y
 n





v   nuv uv 
uv uv
nuv nuv 
n

N
u

R
u

{
R

B
}
v

{
R

B
}
n

N
u

{
R

B
}
v

{
R

B
}






28
UL
29 UL
 min      nruv
ynuv
    nuv
ynuv

n

N
r

R
u

{
R

B
}
v

{
R

B
}
n

N
u

{
R

B
}
v

{
R

B
}




30
UL UL
31
UL

y



C






uv
nuv
n
uv
uv
uv
 u{ R  B} v{R  B}

nN
u{ R  B } v{ R  B }


 
(Sub 3.9)
Subject to:
0  uvUL  
u , v  {R  B}
(Sub 3.9.1)
UL
ynuv
 0 or 1
n  N , u, v  {R  B}
(Sub 3.9.2)
Subproblem 10 (related to decision variable ztDL )
Z sub ( 15 )




15
DL 
 min     nuv


z
  tuv t  

 bB tTb

nN u{R B} v{R B}

(Sub 3.10)
Subject to:
ztDL  0 or 1
t  Tb , b  B
(Sub 3.10.1)
z
n  N , s  {R  B}
(Sub 3.10.2)
tTb
DL
t
1
Subproblem 11 (related to decision variable ztUL )
Z sub ( 29 )



29
UL 
 min     nuv


z
  tuv t  
n

N
u

{
R

B
}
v

{
R

B
}
 bB tTb
 

(Sub 3.11)
Subject to:
ztUL  0 or 1
t  Tb , b  B
(Sub 3.11.1)
z
n  N , s  {R  B}
(Sub 3.10.2)
tTb
UL
t
1
Thanks for Your Listening
2016/6/13
OPLab, IM, NTU
57